This invention relates to the field of content delivery. More specifically the invention relates to delivering large payloads (i.e., files) closer to users in a network environment.
Content delivery in a network environment involves sending information (e.g., in the form of a file) from a content provider to multiple content servers which may serve their content to multiple users residing at various destinations on the network. The content provider generally puts the information that is to be distributed onto a computer connected to a network. This computer is often referred to as a content server. Any client-server or peer-to-peer communication protocols may be applied for a content server to further transfer the information to a group of content servers in the same or different networks that are assigned to serve the information. The source content server is usually called the origin server. The information resides in a file on a content server and is available to users of the network. When users request access to the information, the contents of the file are delivered from any of the content servers that are assigned to serve the content to the requesting users using the desired file transfer protocol (i.e., method of transfer). A content server may receive the information from an origin server before any user request, or it may retrieve the information from an origin server upon user request. A content server may be assigned to serve information from multiple origin servers, and an origin server may forward only part of its information to a set of content servers. The owner of the content servers is usually called content delivery network (CDN) provider. In a network such as the Internet, for example, a user may access the network via an Internet Service Provider (ISP) connecting through a central office (CO) of a telephone company or a head end (HE) of a cable company. Thus, the ISP acts as the user's gateway to the Internet. Examples of ISPs include America On Line™ (AOL™) and Earthlink™. Some telephone companies and cable companies are also ISPs. ISPs may interconnect to each other's network, they may connect to a backbone provider, telephone company's network, cable company's network, or any private or public network. Backbone providers provide high bandwidth connectivity for ISPs, enterprise, etc. Through the ISP, CO, or HE, the user may access services (e.g., data) available from content providers from any content servers in the network.
Various types of data (i.e., information) may be transmitted over a network. For example, when a user desires access to web pages, text documents, application programs, static images, audio, video, or any other type of data available from a remote content server, the contents of the files containing the desired data (i.e., information) must then be delivered to the user from the content server. Files containing web pages and text documents are generally small compared to some other file types, such as files containing video or multimedia data. Therefore, transferring a web page from a content server in a remote location, such as Australia, to a user in United States may take less than a few seconds. However, transferring a video file, for example, may take minutes to hours depending on the size of the video file and the speed of the users connection. Such transfers place a huge demand on the network that may result in lost data. For example, when data is sent across the Internet the receiving system may not receive all of the data transmitted from the content server. This is because the data packets (data is generally transferred in packets) may pass through some routers where some packets may be dropped due to congestion. The receiving system notifies the server of the missing data so that it may resend the data. In some cases, dropped packets can slow or halt the delivery of content because if many servers keep resending data to their clients, the routers get even more congested and thus more dropped packets.
Network-based content delivery that relies on a single source to simultaneously distribute various types of information to multiple remote locations may, depending on the size of files being transferred, encounter network-loading problems around the server or the server itself may be over tasked. For example, since transferring a small file (e.g., a web-page) usually takes only a few seconds, the massive distribution of a small file from one source to thousands of destination locations may not create large impact on the network traffic near the source. Transferring a large file (i.e., a large payload), in contrast, can take tens of minutes to hours. If the distribution of such payloads relies on a single source, the network performance near the source, and the subsequent delivery of content, could degrade severely and become unacceptable.
Therefore, while it may be acceptable to rely on a single source to distribute small files (e.g., web pages, text, or small images), the potential for server and/or network overload calls for using multiple sources to distribute large files to multiple clients.
The fast-paced expansion of the broadband industry has fueled the push for rich media (e.g., full length movies, video, or other types of multimedia data). Broadband technology brings high-speed connection capabilities for content delivery to remote users hence large payloads can be transferred faster. Also, broadband technology makes it possible to send audio and/or video data using streaming media whereby the data is sent in streams for real-time playback, for example. Thus, the quality of rich media at the user's terminal, more than that of any other type of information, is now more dependent on the performance capabilities of the delivery technology. In order to minimize delivery delays, network congestion, and other related problems, some systems attempt to locate content on server systems that are located in close proximity to, i.e., a few hubs of connections away from the end-users. These server locations approximately define the concept known as the “edge” of the network. For example, the Internet service providers are in close proximity to the end-user thus may be regarded as being at the edge of the network. When servers are placed in such locations, the servers are said to be at the edge of the network. End-user systems that are configured to obtain content from network nodes located at the edge of the network are therefore beyond the edge of the network (a.k.a. last mile). However, it is important to note that systems located beyond the edge of the network are still coupled to the network and capable of communicating with the server computers located at the edge. Placing content at the edge of the network is advantageous because it can reduce the latency in servicing users located beyond the edge. Current approaches for delivering large payloads to the “edge” consist of mirroring or caching. These approaches and the limitations inherent in each approach will now be discussed in detail so as to give the reader an understanding of the advancements made by the invention.
Caching
A simple example of caching is web caching. In its simplest form, web caching involves a cache appliance located between a client user and an origin server such that data fetched once from the origin server is saved in the cache device (appliance) to service subsequent requests for the same data. An illustration of caching is shown in FIG. 1, for example. A client user at browser 104 in Local Area Network (LAN) 108 desiring to obtain data available from origin server 100 enters the Universal Resource Locator (URL) address of the desired data into browser 104. LAN 108 may be an ISP's network, for example. The request is forwarded to cache appliance 102, which is an HTTP (Hyper Text Transport Protocol) proxy server in this illustration. The proxy server which may, for example, be owned by the ISP is typically located at the ISP's local network. Like any other server, proxy servers (cache appliance) 102 and 103 are computers with local processing and memory. A subset of that memory is known as the proxy cache. Cache is generally used as temporary storage for frequently used information. Note that, although only one cache appliance is shown in each ISP's local area network of FIG. 1, an actual implementation may have more than one cache appliance in an ISP's local area network.
Proxy server (i.e., cache appliance) 102 processes the request received from client at browser 104 and searches its cache (i.e., memory) for the requested data, if the data is not available in its cache, proxy server 102 forwards the request to origin server 100 via network router 101. In this illustration, network router 101's sole purpose is to forward requests to origin server 100. Origin server 100 is an HTTP server with single TCP/IP (Transmission Control Protocol/Internet Protocol) connection path 110 to client user at browser 104.
Origin server 100 services the request and forwards the requested data to cache appliance 102. Upon receipt of the data, cache appliance 102 may save the data in its local cache memory and also forwards it to browser 104. The data is said to be cached in HTTP proxy (cache appliance) 102. A subsequent client user at browser 105 desiring the same data gets their request serviced by HTTP proxy server (cache appliance) 102 without the request being forwarded to HTTP server 100. However, users 106 and 107 at LAN 109 requesting the same data would have their initial request serviced by HTTP server 100 because users 106 and 107 are not connected through HTTP proxy 102 which has the data cached in memory. Instead, HTTP proxy 103 would perform the same processes as discussed above for HTTP proxy 102 to obtain and cache the data in its memory. Thus, proxy servers 102 and 103, which are said to be at the edge of the network, are populated upon user demand.
Once the data is cached in HTTP proxy 102 and 103, origin server 100 would not need to service requests for the same data from users connecting through HTTP proxy servers 102 and 103. By caching the data at various proxy servers closer to the users, delivery of content is distributed thereby reducing the load around the network server. However, caching is only good for delivering static content data that is fixed in memory such as static web pages. Caching does not work for dynamic information such as services (e.g., functions, transactions, etc.), streaming media, or any other type of dynamic information.
The HTTP protocol is well known to those of ordinary skill in the arts; therefore software to perform the caching function at HTTP proxy servers 102 and 103 is readily available. However, this is not the case with streaming media because different providers of streaming servers use differing protocols to transmit data to the recipient player (e.g., a browser). FIG. 2 is an illustration of a typical streaming server connection to a player.
In contrast to HTTP TCP/IP connections to the browser, Streaming server 200 is connected to player 201 via three connection paths. Path 202 is the Real-Time Streaming Protocol (RTSP) connection. RTSP is a protocol that provides for control over delivery of data with real-time properties such as audio and video streams. RTSP contains a description of media data and provides playback controls such as play, rewind, fast-forward, and pause to player 201. Playback may be done with an offset so that a player can start receiving the data from a specified point. For example, when player 201 rewinds, a different offset, corresponding to the desired playback position, is sent to streaming server 200 and incoming data is sent through path 203 starting from the new offset. Path 203 utilizes the Real-Time Transport Protocol (RTP) and may contain the data being played back. The third connection, path 204, utilizes the RTP Control Protocol (RTCP) and it may provide flow control of the data.
Caching does not work well for streaming media because the various providers of streaming servers use differing intelligence to compute the data being sent over connection 203 as a function of the offset and the flow control. Moreover, server providers do not follow a common standard, therefore placing a cache appliance between streaming server 200 and player 201 would not be readily feasible unless the intelligence, which in today's implementation is in the streaming server, is included either in the streams of information being sent over the connection paths, or if the cache appliance contains the intelligence used by every streaming server provider. Thus, existing systems do not currently provide a viable way to cache streaming media data. Also, since caching is usage based, when content is not cached the proxy will need to fetch the content hence there is a potential for misses and there is no guarantee of quality.
Despite these limitations, caching has advantages such as ease of growth because a new cache appliance can be added anywhere and it will be up and running; a cache appliance can be shared by different content providers; and a cache appliance is very lightweight (i.e., does not require special configuration) and thus easier to manage.
Mirroring
Mirroring is a scheme for providing content-delivery to users at the “edge” of the network that addresses many of the limitations of centralized systems by replicating content to the edge of the network, thereby minimizing the distance between where content is requested and where it is served. In so doing, mirroring saves network bandwidth as compared to delivery to multiple users from one centralized source. The fundamental principles underlying mirroring includes central control of content and the network, efficient distribution of content to the servers at the edge of the network, and automatic redirection of content requests from a user to a local edge server.
In mirroring, file servers are placed throughout the network (e.g., Internet), close to where the content requests originate. This principle mirrors some of the functionality of caches, but with distinct differences. In particular, these file servers work together in a centrally controlled collaborative fashion to ensure overall network performance. Like a cache, content is replicated from the origin server to the server only once, regardless of the number of times the content is served. However, mirroring provides greater content control. By pre-populating the server, the content will be available for fast delivery to the user, eliminating cache misses and increasing the hit rate. Mirroring, in combination with caching, delivers a better-integrated solution with the benefits of both approaches.
One URL applies to all the servers in a mirroring implementation. When a browser requests the URL, the system determines a local delivery server based on: geographical and network location; presence of content; and current status of server (both availability and load).
FIG. 3 is an illustration of a network content delivery scheme employing mirroring to push content to the edge of the network. Assuming boundary 300 represents the edge of the network, mirroring locates file servers (e.g., FS 301–308) at the edge, as shown in FIG. 3. In this illustration, File Server 301 is the master server controlling all other file servers (e.g., 302–308). All content that needs to be pushed to the edge are loaded into master server 301, and then replicated into all the other file servers 302–308 using a preferred push method. For example, the content could be replicated using the multicast method discussed below.
Unlike caching, where the content must be static (i.e., does not change with time), mirroring works well for non-static data such as transactions because transaction data can be synchronized from the master server (e.g., FS 301) to the file servers at the edge of the network (e.g., FS 302–308). The various methods of replicating data to file servers at the edge may include broadcast, a transmission from the master server to all listening file servers in the network; anycast, a transmission to the nearest group of servers; unicast, a transmission to a specific receiver; and multicast, a transmission to multiple specific receivers (a more detailed discussion of multicasting is discussed below). Once content is delivered at the edge, a user at browser 330 requesting access to content is automatically routed to the geographically closest server (e.g., server 307) that is able to service that request.
Mirroring also works well for streaming media. Streaming servers can be attached to any of file servers 301–308 to provide service closest to where it is needed. For example, by attaching a streaming server 310 to file server 302 a user at player 320, in the geographic vicinity of file server 302, can playback streaming media data without much latency. Thus, in mirroring implementations, streaming servers can be attached to any of the file servers to overcome the limitations of caching. However, current methods suffer significant disadvantages, for example, a large object such as video that is popular may create a hotspot on a disk because of repeated access to the content and because disk input/output bandwidth is limited. Moreover, the large object needs to be fully transferred to either the application server or the cache appliance before satisfaction of an end-user client request for the data may commence thereby creating potential latency issues.
Mirroring, also, can be very expensive due to scalability issues, storage limitations, management costs, and inadequate load balancing. Scalability issues arise from the need to store entire large files, such as video, within a storage media. Therefore, new storage must be added to all the file servers in the network when available storage is inadequate for storing a particular large file. Since all the file servers in the network must maintain the same file configuration, upgrading all the file servers in the mirroring environment could prove to be very expensive. Additionally, new file servers brought into the network would need to be configured to conform to all other file servers in the network.
Adding more storage requires rack space for mounting the new storage devices. Rack space is usually limited and sometimes expensive. Moreover, as storage capacity increases, more system administration functions (e.g., backup) are needed to manage the configuration. Since cost of system administration is expensive and rack space is limited, mirroring suffers.
Content Distribution Using Multicast
Multicast is simultaneous communication between a single sender and multiple selected receivers on a network. FIG. 4 is an illustration of a distribution network that uses multicast technology to push information to multiple content servers on a network.
The source provider uploads the large payload (e.g., video file, image data, or any other file having a size significant enough to strain network resources) onto the root server 400 which may be, for example, a content server located in Los Angeles. The root server may also be referred to as the origin server. Root server 400 subsequently multicasts the video data to multiple servers (e.g., servers 401 through 403) that are at the second level of the network server tree, usually in differing geographical locations. For example, server 401 may be located in San Diego, server 402 in San Jose, and server 403 in San Francisco. After receiving the video data, servers 401 through 403 will multicast the video data to servers in the next level of the server tree. For example, server 401 multicasts the data to servers 404 through 406, server 402 multicasts the data to servers 407 through 409, and server 403 multicasts the data to servers 410 through 412. In this illustration, each server multicasts to three other servers, however, most implementations involve multicast to more than three servers (e.g., ten servers).
After the video data is distributed amongst servers 400 through 412, the video data becomes available from multiple servers that are located in different geographical localities on the network. This distribution method pushes content to the edge into a mirroring type architecture where user requests may be serviced from one of multiple servers, usually from the geographically closest server. Multicasting the entire large payload file may still cause congestion due to insufficient capacity on a particular communication link; network equipment congestion due to processing speed of networking equipment; server congestion due to data processing speed of the server; and latency in the network due to the time associated with the data traveling over long distances.
Load Balancing
Load balancing is the task of distributing the network load and the processing load to a cluster of servers to improve system performance, while simultaneously increasing the reliability of the service provided by the servers. A load balancer is often implemented as either a switch or a router and called a load balancing switch or a load balancing router respectively. A load balancer's network interface, the Virtual IP address (VIP), serves as a virtual external interface for the server cluster. Each server in a cluster has both an internal (local IP address) and an external (IP address) network interface. Most load balancers provide a feature called Network Address Translation (NAT), which translates VIP to a local IP address, which are useable on the Internet. A load balancer accepts all data packets addressed to its VIP, and distributes them equally to the most available servers.
A load balancer maintains a state table (e.g., what server is servicing what client), so that data packets of a persistent session flow to and from the same client and server end points. Many load balancers have a configurable “sticky” feature that distributes data packets from a client to the same server that the client was previously connected to. The “sticky” feature allows a server to intelligently prepare for possible future requests from its clients.
Load balancers can typically operate in either a “regular” (i.e., non-transparent) mode or a “transparent” mode. The difference between “regular” mode and “transparent” mode lies in the management of inbound and outbound data flow. In “regular” mode, all inbound traffic to and outbound traffic from the server cluster passes through the load balancer. In “transparent” mode, outbound traffic from the server cluster bypasses the load balancer by flowing directly through an IP router. The “transparent” mode can be extremely important for a network of servers delivering large amounts of data, as it reduces the overall load on the load balancing router and thus improves network performance. When a load balancer is operating in “transparent” mode, it does not translate the destination IP in the inbound packets from clients to its server cluster. An IP router must be connected both to the load balancer and the server cluster to do this. The servers in the server cluster are then configured with a loop back interface using the IP address of the load balancer and with a default route to the IP router.
Most load balancers provide either a remote or local Application Programming Interface (API) or scripts to manage their load balancing tasks. In general, current technology uses a round-robin approach (i.e., the next server in the queue services the next client) to load balance a cluster of available servers. This may mean that servers are allocated tasks even if they don't have available bandwidth.
Therefore, there is a need to address the cost, scalability, and load-balancing issues associated with large payload delivery to the edge of the network. However, before discussing the present invention, a general overview of how files are handled in different operating systems is presented.
File Configuration on Computer Systems
The overall structure in which files are named, stored, organized and accessed in an operating system is referred to as a “file system”. In the UNIX operating system, for example, each directory can be mounted with a file system. If a directory /X is mounted with file system Y, any storage I/O (Input/Output) request within the sub-tree /X is forwarded to the file system Y. For example, opening of a file /X/foo.txt causes the open request to be forwarded to the corresponding “open” routine in file system Y.
Contemporary operating systems, such as Unix and Windows, support “stackable file systems”. A stackable file system is a file system that is built on top of another file system. For example, if a stackable file system F is built above file system K, and if directory /X is mounted with F, then opening of a file /X/foo.txt causes the open request to go to file system F. File system F processes the request and it may or may not generate a request to file system K. In the Windows operating system environment, a stackable file system is called a file filter. A file filter can be placed on any directory. Any I/O access to a directory that has a file filter causes a corresponding file filter routine to be executed. A file filter may or may not send any request to the underlying file system.
A distributed file system is one in which files may be located on multiple servers connected over a local or wide area network. A distributed file system can be implemented using any one of several well-known network file system protocols, e.g., the Common Internet File System (CIFS) and Sun Microsystems, Inc.'s Network File System (NFS) protocol. CIFS is based on the standard Server Message Block (SMB) protocol widely in use by personal computers and workstations running a wide variety of operating systems. The CIFS protocol supports a number of file sharing and representation features, such as: file access, file and record locking, safe caching, read-ahead, and write-behind, file change notification, protocol version negotiation, extended attributes, distributed replicated virtual volumes, and server name resolution. NFS, like CIFS, is intended to provide an open cross-platform mechanism for client systems to request file services from server systems over a network. The NFS protocol provides transparent remote access to shared files across networks because it is designed to be portable across different machines, operating systems, network architectures, and transport protocols. NFS' portability is achieved through the use of Remote Procedure Call primitives (RPC primitives) that are built on top of system implementations that use the External Data Representation standard (XDR). The RPC primitives provide an interface to remote services. A server supplies programs (e.g., NFS), each program including a set of procedures. The combination of a server's network address, a program number, and a procedure number specifies a specific remote procedure to be executed. XDR uses a language to describe data formats. The language can only be used to describe data; it is not a programming language. NFS Implementations exist for a wide variety of systems. NFS mount protocol allows the server to hand out remote access privileges to a restricted set of clients and to perform various operating system-specific functions that allow, for example, attaching a remote directory tree to a local file systems.
The above examples illustrate the limitations and problems associated with current systems for distributing large files. Because of these problems there is a need for a method and apparatus that utilizes a more effective means for delivering large payloads.